Field of the Invention
The present invention relates to an image reconstruction process of an image diagnostic apparatus that forms a tomographic image in an object.
Description of the Related Art
An image diagnostic apparatus that forms a tomographic image in an object forms a tomographic image using radiation. The tomographic image is used for diagnosis of a patient by a doctor or the like. Such an image diagnostic apparatus performs an image reconstruction process to obtain the tomographic image. An image diagnostic apparatus such as an X-ray computed tomography (CT) apparatus, a positron emission tomography (PET) apparatus, or a single photon emission CT (SPECT) apparatus includes projection calculation in the image reconstruction process.
Image reconstruction processing methods including projection calculation are roughly divided into analytical methods and successive approximation. In the analytical methods, the processing load is light, but the quality of a reconstructed image is low. In the successive approximation, although the processing load is heavy, the image quality can be expected to be improved by reducing noise on a reconstructed image. One of the successive approximation image reconstruction methods is a block iteration type successive approximation image reconstruction method.
Conventionally, when performing the image reconstruction process using a plurality of operation units, measurement data (tomogram data of an object) obtained by the image diagnostic apparatus is distributed among the operation units, and after that, the plurality of operation units perform parallel processes, as described in Japanese Patent Laid-Open No. 2011-72827. In this case, if an image region (image space) to be calculated can be specified from the measurement data, only the image region is distributed among the operation units. If the image region cannot be specified, the data of the whole image region is distributed among the operation units. In addition, to shorten the data transfer time among the operation units, divided images are distributed to the operation units, and parallel processes are performed, as described in Zakaria Bahi, Julien Bert, Awen Autret and Dimitris Visvikis, “High Performance Multi-GPU Acceleration for Fully 3D List-Mode PET Reconstruction”, 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, 2012.
When forming a detailed tomographic image in an object, measurement data (tomogram data of the object) is obtained in a large scale. Hence, an image reconstruction processing method for handling the large-scale measurement data using a plurality of operation units is indispensable. However, since an image reconstruction process using the large-scale measurement data or reconstructed image data is performed, the data amount exceeds the memory size of the operation units.